# AI use cases for Awesome Robot Use Agent (kairunwen/Awesome-Robot-Use-Agent) Repo: [kairunwen/Awesome-Robot-Use-Agent](https://github.com/kairunwen/Awesome-Robot-Use-Agent) | Use cases: 4 | Page: https://dedupedai.com/use-cases/kairunwen-awesome-robot-use-agent/ A curated GitHub list of papers, articles, open-source tools, benchmarks, and community demos for robot-use agents, which are AI systems that plan and act through robots. This file holds every use case of this repo. Each one starts with a "## " heading and ends with its URL. - Map the robot-use agent field from current surveys: https://dedupedai.com/use-cases/kairunwen-awesome-robot-use-agent/map-robot-use-agent-field-from-surveys/ - Shortlist a robot-use method for a manipulation project: https://dedupedai.com/use-cases/kairunwen-awesome-robot-use-agent/pick-robot-use-method-for-manipulation-project/ - Choose benchmarks to test a robot-use agent: https://dedupedai.com/use-cases/kairunwen-awesome-robot-use-agent/choose-benchmarks-to-test-robot-use-agent/ - Prototype a voice and camera desktop robot agent: https://dedupedai.com/use-cases/kairunwen-awesome-robot-use-agent/prototype-voice-camera-desktop-robot-agent/ ## How to map the robot-use agent field from current surveys with Awesome Robot Use Agent Repo: [kairunwen/Awesome-Robot-Use-Agent](https://github.com/kairunwen/Awesome-Robot-Use-Agent) | Difficulty: Beginner | Time: 30 minutes | Basis: From the README Read the survey papers to learn the main approaches, terms, and open problems in robot-use agents. **Who it is for:** A graduate student or product lead who is new to robot-use agents and needs a fast overview before choosing a research or build direction. **The problem:** Robot-use agent work is spread across papers, blogs, and demos, and it is hard to tell which terms and categories matter. **The outcome:** A short written map of the field that names the main categories, the survey sources, and the open challenges. ### Steps 1. Open the Articles section and read the Robot-Use Agents perspective to get the core definition. 2. Open the Surveys section and read the two 2026 surveys, Towards Agentic Robots and Survey on Multimodal Embodied Agents, which list their own taxonomies. 3. Read the Towards Embodied Agentic AI review for how LLM and VLM agents connect to robot APIs and ROS. 4. Write down the categories and terms the surveys use, such as PAPAV or the four domains of Model, Data, Environment, and Harness. 5. List the open problems the surveys mention, such as physical constraints and benchmark coverage. ### Prompt to paste into your agent ```text Using the Awesome-Robot-Use-Agent README at https://github.com/kairunwen/Awesome-Robot-Use-Agent, read the Surveys section and produce a one-page summary of the categories and open problems named in the two 2026 surveys for . Verify each claim against the linked survey entry and note any claim the README does not support. ``` ### Caveat The list summarizes each paper from the README text, so read the linked paper before relying on any specific taxonomy. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/kairunwen-awesome-robot-use-agent/map-robot-use-agent-field-from-surveys/ ## How to shortlist a robot-use method for a manipulation project with Awesome Robot Use Agent Repo: [kairunwen/Awesome-Robot-Use-Agent](https://github.com/kairunwen/Awesome-Robot-Use-Agent) | Difficulty: Intermediate | Time: 45 minutes | Basis: From the README Compare listed methods and their evaluation settings to pick one to reproduce or adapt. **Who it is for:** A robotics engineer starting a long-horizon manipulation project who needs a method that fits the robot and task. **The problem:** Many method papers look similar in the abstract, and it is unclear which ones fit a given robot, task length, or failure mode. **The outcome:** A ranked shortlist of two or three methods with the benchmarks each was evaluated on and the code status the README reports. ### Steps 1. Open the Methods & Frameworks section and list the entries that mention long-horizon or manipulation tasks. 2. For each candidate, note the evaluation benchmarks and real-world tasks listed in its summary. 3. Check the Details and sources notes to see whether code or checkpoints are released or listed as forthcoming. 4. Rank the candidates by fit to your robot, your task length, and the release status. 5. Open the paper link for the top two candidates and confirm the claims before you commit. ### Prompt to paste into your agent ```text Use the Methods & Frameworks section of https://github.com/kairunwen/Awesome-Robot-Use-Agent to shortlist two or three methods for >. Output a table with method name, evaluation benchmarks, and code release status as stated in the README. Verify that each code status matches the Details and sources note for that entry. ``` ### Caveat The README records author-reported results and release status, so independent reproduction is still needed before adoption. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/kairunwen-awesome-robot-use-agent/pick-robot-use-method-for-manipulation-project/ ## How to choose benchmarks to test a robot-use agent with Awesome Robot Use Agent Repo: [kairunwen/Awesome-Robot-Use-Agent](https://github.com/kairunwen/Awesome-Robot-Use-Agent) | Difficulty: Intermediate | Time: 60 minutes | Basis: From the README Pick simulation benchmarks from the list that match your robot and task before you run tests. **Who it is for:** An AI engineer evaluating a robot-use agent who needs a fair test set before comparing results. **The problem:** A robot-use agent can look strong on one benchmark and weak on another, and choosing the wrong suite gives misleading results. **The outcome:** A short evaluation plan that names two or three benchmarks, the task types each covers, and the links to their sources. ### Steps 1. Open the Benchmarks section and list every benchmark with its task type, such as manipulation, navigation, or mobile manipulation. 2. Match each benchmark to the tasks your agent must perform. 3. Check the Methods & Frameworks notes to see which benchmarks similar methods were evaluated on. 4. Write a plan with two or three benchmarks, each with a reason tied to your task. 5. Follow the links to each benchmark site to confirm its setup requirements before you install anything. ### Prompt to paste into your agent ```text Read the Benchmarks section of https://github.com/kairunwen/Awesome-Robot-Use-Agent and recommend two or three benchmarks for testing a robot-use agent that must . Output the benchmark names, the task type each covers, and the README link for each. Verify each benchmark name appears in the README before you recommend it. ``` ### Caveat The README lists benchmarks but does not give setup commands, so each benchmark's own documentation is needed to run it. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/kairunwen-awesome-robot-use-agent/choose-benchmarks-to-test-robot-use-agent/ ## How to prototype a voice and camera desktop robot agent with Awesome Robot Use Agent Repo: [kairunwen/Awesome-Robot-Use-Agent](https://github.com/kairunwen/Awesome-Robot-Use-Agent) | Difficulty: Advanced | Time: 2 hours | Basis: From the README Follow the linked tutorial to connect a language model to a desktop robot with voice and vision. **Who it is for:** A developer or maker with a Reachy Mini who wants an interactive desktop robot that listens, sees, and acts. **The problem:** Wiring reasoning models, speech input, camera input, and robot actions together takes time without a reference path. **The outcome:** A working desktop robot prototype that responds to voice and camera input through tool calling. ### Steps 1. Open the Articles section and read the NVIDIA and Hugging Face tutorial on Reachy Mini. 2. Follow the tutorial to set up the Nemotron reasoning and vision models, NeMo Agent Toolkit, and Pipecat. 3. Connect the Reachy Mini camera and voice input as the tutorial describes. 4. Define one robot behavior as a Python interface and expose it as a ReAct tool. 5. Run a voice command and confirm the robot performs the behavior. ### Prompt to paste into your agent ```text Using the NVIDIA and Hugging Face Reachy Mini tutorial linked in https://github.com/kairunwen/Awesome-Robot-Use-Agent, set up a voice and camera agent for a Reachy Mini and add one robot behavior as a ReAct tool. Report the steps completed and the behavior triggered by one spoken command. Verify the tool call appears in the agent log before you report success. ``` ### Caveat The README links the tutorial but does not reproduce its setup, and the tutorial targets a desktop robot rather than general manipulation. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/kairunwen-awesome-robot-use-agent/prototype-voice-camera-desktop-robot-agent/